Revised diagnostic criteria for neurofibromatosis type 1 and Legius syndrome: an international consensus recommendation

Purpose By incorporating major developments in genetics, ophthalmology, dermatology, and neuroimaging, to revise the diagnostic criteria for neurofibromatosis type 1 (NF1) and to establish diagnostic criteria for Legius syndrome (LGSS). Methods We used a multistep process, beginning with a Delphi method involving global experts and subsequently involving non-NF experts, patients, and foundations/patient advocacy groups. Results We reached consensus on the minimal clinical and genetic criteria for diagnosing and differentiating NF1 and LGSS, which have phenotypic overlap in young patients with pigmentary findings. Criteria for the mosaic forms of these conditions are also recommended. Conclusion The revised criteria for NF1 incorporate new clinical features and genetic testing, whereas the criteria for LGSS were created to differentiate the two conditions. It is likely that continued refinement of these new criteria will be necessary as investigators (1) study the diagnostic properties of the revised criteria, (2) reconsider criteria not included in this process, and (3) identify new clinical and other features of these conditions. For this reason, we propose an initiative to update periodically the diagnostic criteria for NF1 and LGSS

The role of artificial intelligence in paediatric neuroradiology

Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping of neuroradiologic conditions is becoming increasingly prevalent, particularly with radiogenomic analyses correlating imaging characteristics with molecular biomarkers of disease. However, integration into routine clinical practice remains elusive. With modern multi-parametric MRI now providing additional data beyond anatomy, informing on histology, biology and physiology, such metric-rich information can present as information overload to the treating radiologist and, as such, information relevant to an individual case can become lost. Artificial intelligence techniques are capable of modelling the vast radiologic, biological and clinical datasets that accompany childhood neurologic disease, such that this information can become incorporated in upfront prognostic modelling systems, with artificial intelligence techniques providing a plausible approach to this solution. This review examines machine learning approaches than can be used to underpin such artificial intelligence applications, with exemplars for each machine learning approach from the world literature. Then, within the specific use case of paediatric neuro-oncology, we examine the potential future contribution for such artificial intelligence machine learning techniques to offer solutions for patient care in the form of decision support systems, potentially enabling personalised medicine within this domain of paediatric radiologic practice

Neuroimaging manifestations in children with SARS-CoV-2 infection: a multinational, multicentre collaborative study

The CNS manifestations of COVID-19 in children have primarily been described in case reports, which limit the ability to appreciate the full spectrum of the disease in paediatric patients. We aimed to identify enough cases that could be evaluated in aggregate to better understand the neuroimaging manifestations of COVID-19 in the paediatric population. An international call for cases of children with encephalopathy related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and abnormal neuroimaging findings was made. Clinical history and associated plasma and cerebrospinal fluid data were requested. These data were reviewed by a central neuroradiology panel, a child neurologist, and a paediatric infectious diseases expert. The children were categorised on the basis of their time of probable exposure to SARS-CoV-2. In addition, cases were excluded when a direct link to SARS-CoV-2 infection could not be established or an established alternate diagnostic cause could be hypothesised. The accepted referral centre imaging data, from ten countries, were remotely reviewed by a central panel of five paediatric neuroradiologists and a consensus opinion obtained on the imaging findings. 38 children with neurological disease related to SARS-CoV-2 infection were identified from France (n=13), the UK (n=8), the USA (n=5), Brazil (n=4), Argentina (n=4), India (n=2), Peru (n=1), and Saudi Arabia (n=1). Recurring patterns of disease were identified, with neuroimaging abnormalities ranging from mild to severe. The most common imaging patterns were postinfectious immune-mediated acute disseminated encephalomyelitis-like changes of the brain (16 patients), myelitis (eight patients), and neural enhancement (13 patients). Cranial nerve enhancement could occur in the absence of corresponding neurological symptoms. Splenial lesions (seven patients) and myositis (four patients) were predominantly observed in children with multisystem inflammatory syndrome. Cerebrovascular complications in children were less common than in adults. Significant pre-existing conditions were absent and most children had favourable outcomes. However, fatal atypical CNS co-infections developed in four previously healthy children infected with SARS-CoV-2. Acute-phase and delayed-phase SARS-CoV-2-related CNS abnormalities are seen in children. Recurring patterns of disease and atypical neuroimaging manifestations can be found and should be recognised being as potentially due to SARS-CoV-2 infection as an underlying aetiological factor. Studies of paediatric specific cohorts are needed to better understand the effects of SARS-CoV-2 infection on the CNS at presentation and on long-term follow-up in children. American Society of Pediatric Neuroradiology, University of Manchester (Manchester, UK). VIDEO ABSTRACT

Appendiceal involvement in pediatric inflammatory multisystem syndrome temporally associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2):a diagnostic challenge in the coronavirus disease (COVID) era

BACKGROUND: Many studies on pediatric inflammatory multisystem syndrome temporally associated with severe acute respiratory syndrome coronavirus 2 (PIMS-TS) have described abdominal findings as part of multisystem involvement, with limited descriptions of abdominal imaging findings specific to PIMS-TS.OBJECTIVE: To perform a detailed evaluation of abdominal imaging findings in children with PIMS-TS.MATERIALS AND METHODS: We performed a single-center retrospective study of children admitted to our institution between April 2020 and January 2021 who fulfilled Royal College of Paediatrics and Child Health criteria for PIMS-TS and who had cross-sectional abdominal imaging. We studied clinical data, abdominal imaging, laboratory markers, echocardiography findings, treatment and outcomes for these children. We also reviewed the literature on similar studies.RESULTS: During the study period, 60 PIMS-TS cases were admitted, of whom 23 required abdominal imaging. Most (74%) were from a Black, Asian or minority ethnic background and they had an average age of 7 years (range 2-14 years). All children had fever and gastrointestinal symptoms on presentation with elevated C-reactive protein, D-dimer and fibrinogen. Most had lymphopenia, raised ferritin and hypoalbuminemia, with positive severe acute respiratory syndrome coronavirus 2 immunoglobulin G antibodies in 65%. Free fluid (78%), right iliac fossa mesenteric inflammation (52%), and significantly enlarged mesenteric lymph nodes (52%) were the most common imaging findings. Appendiceal inflammation (30%) and abnormal distal ileum and cecum/ascending colon wall thickening (35%) were also common. All children responded well to medical management alone, with no mortality.CONCLUSION: In addition to free fluid, prominent lymphadenopathy, and inflammatory changes in the right iliac fossa, we found abnormal long-segment ileal thickening and appendicitis to be frequent findings. Recognition of appendiceal involvement as a component of the PIMS-TS spectrum should help clinicians avoid unnecessary surgical intervention as part of a multidisciplinary team approach.</p

<i>NF2</i>-related schwannomatosis and other schwannomatosis: an updated genetic and epidemiological study

Peer reviewed: TrueFunder: NHS EnglandFunder: NIHRFunder: National Institute for Health ResearchObjectivesNew diagnostic criteria for NF2-related schwannomatosis (NF2) were published in 2022. An updated UK prevalence was generated in accordance with these, with an emphasis on the rate of de novo NF2 (a 50% frequency is widely quoted in genetic counselling). The distribution of variant types among de novo and familial NF2 cases was also assessed.MethodsThe UK National NF2 database identifies patients meeting updated NF2 criteria from a highly ascertained population cared for by England’s specialised service. Diagnostic prevalence was assessed on 1 February 2023. Molecular analysis of blood and, where possible, tumour specimens forNF2, LZTR1andSMARCB1was performed.Results1084 living NF2 patients were identified on prevalence day (equivalent to 1 in 61 332). The proportion with NF2 inherited from an affected parent was only 23% in England. If people without a confirmed molecular diagnosis or bilateral vestibular schwannoma are excluded, the frequency of de novo NF2 remains high (72%). Of the identified de novo cases, almost half were mosaic. The most common variant type was nonsense variants, accounting for 173/697 (24.8%) of people with an established variant, but only 18/235 (7.7%) with an inheritedNF2pathogenic variant (p&lt;0.0001). Missense variants had the highest proportion of familial association (56%). The prevalence ofLZTR1-related schwannomatosis andSMARCB1-related schwannomatosis was 1 in 527 000 and 1 in 1.1M, respectively, 8.4–18.4 times lower than NF2.ConclusionsThis work confirms a much higher rate of de novo NF2 than previously reported and highlights the benefits of maintaining patient databases for accurate counselling.</jats:sec

Neuroimaging manifestations in children with SARS-CoV-2 infection: a multinational, multicentre collaborative study

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